Broad-scale Spatial Patterns Research Articles

Advancements in monitoring: a comparison of traditional and application-based tools for measuring outdoor recreation.

Outdoor recreation has experienced a boom in recent years and continues to grow. While outdoor recreation provides wide-ranging benefits to human well-being, there are growing concerns about the sustainability of recreation with the increased pressures placed on ecological systems and visitor experiences. These concerns emphasize the need for managers to access accurate and timely recreation data at scales that match the growing extent of the recreation footprint. Here, we compare spatial and temporal patterns of winter and summer recreation using traditional (trail cameras, infrared counters, aerial surveys, participatory mapping) and application-based tools (Strava Metro, Strava Global Heatmap, Wikiloc) across the Columbia and Canadian Rocky Mountains of western Canada. We demonstrate how recreation use can be estimated using traditional and application-based tools, although their accuracy and utility varies across space, season and activity type. We found that trail cameras and infrared counters captured similar broad-scale patterns in count estimates of pedestrians and all recreation activities. Aerial surveys captured areas with low recreation intensity and participatory mapping captured coarser information on the intensity and extent of recreation across large spatial and temporal scales. Application-based data provided detailed spatiotemporal information on recreation use, but datasets were biased towards specific activities. Strava Metro data was more suited for capturing broad-scale spatial patterns in biking than pedestrian recreation. Application-based data should be supplemented with data from traditional tools to identify biases in data and fill in data gaps. We provide a comparison of each tool for measuring recreation use, highlight each tools' strengths and limitations and applications to address real-world monitoring and management scenarios. Our research contributes towards a better understanding of which tool, or combinations of tools, to use that can expand the rigor and scope of recreation research. These findings support decision-making to mitigate pressures on wildlife and their habitats while allowing for high-quality recreation experiences.

Broad-scale spatial distribution patterns of soft-sediment macrobenthic communities in the Red Sea

In sub-tropical and tropical regions, the diversity patterns of soft-sediment macrobenthic communities are still poorly understood, particularly when compared to temperate shelf environments. The present study investigates spatial patterns of variability in macrobenthic distribution along the eastern Red Sea margin, and the role of sediment composition and other explanatory variables in determining such patterns. This study has two main objectives: (i) to produce a baseline characterization of the Saudi Arabian Red Sea macrobenthic infauna, particularly along the central and southern regions, (ii) to assess the relative contribution of two major processes driving macrobenthic communities (i.e., dispersal-based and environmental filtering), based on changes on beta-diversity components (turnover and nestedness) across multiple scales (up to ~600km), using relevant modeling methodologies. Shallow soft-sediment macrobenthic communities in the Red Sea showed extremely high small-scale variability, highlighted by the percentage of rare species (44% of species present at a single sample) and the dominance of turnover (species replacement) over nestedness. Our results also suggest a strong influence of broad- over fine-scale variation in the species composition. However, sedimentary characteristics, particularly grain-size, played a critical role governing the distribution patterns of soft-sediment macrobenthic communities in the Red Sea. Our findings highlight the importance of regional factors in shaping the macrofaunal community composition whilst also highlighting the role of high species diversity at local scales. The current results suggest the need for conservation measures from regional levels (to maintain genetic diversity) to local levels (to preserve the high occurrence of rare species). To our knowledge, no other study investigated the distribution of Red Sea marine species over large spatial scales combining modeling methods and the partitioning of beta-diversity. The current approach applied to soft-sediment macroinvertebrates can be extended to other marine communities since conservation strategies can be more effective when mechanisms governing species distribution are considered.

Synanthropic triatomines in Hidalgo state, Mexico: Spatial-temporal distribution, domestic transmission cycle, and natural infection with Trypanosoma cruzi

Triatomine vectors are responsible for the main route of transmission of the protozoan Trypanosoma cruzi, the etiological agent of Chagas disease. This illness is potentially life-threatening and highly disabling and represents a major public health concern in the endemic countries in Latin America. The analysis of the spatial and temporal occurrence of triatomine insects is critical, since control strategies strongly depend on the vector species found within each area. Such knowledge is non-existent in Hidalgo state, an endemic region of Chagas disease in Mexico. A Geographic Information System (GIS) was used to analyze broad-scale spatial and temporal patterns of synanthropic triatomines collected in Hidalgo. Data was taken from the Institute of Epidemiological Diagnosis and Reference (InDRE) of Mexico and the state program of Vector Control of the Secretary of Health, covering the period of 1997–2019. Our analyses demonstrate a differential distribution of Triatoma dimidiata, T. mexicana, T. gerstaeckeri and T. barberi, which are the four predominant species, and that climate, temperature, and precipitation are some of the drivers of their distribution pattern. Notably, we report the presence of T. nitida, T. pallidipennis and T. phyllosoma for the first time in the state. In addition, we found seasonal variations of the populations of T. mexicana and T. gerstaeckeri, but not for T. dimidiata, whose population remains constant throughout the year. The insects were found mainly intradomicile (81.79%), followed by peridomicile (17.56%) and non-domestic areas (0.65%), with an average T. cruzi infection of 16.4%. Based on this evidence, priority sites for vector control intervention were identified. Our findings are very valuable for understanding the epidemiology of Chagas disease, the generation of future potential risk maps and for the development and implementation of effective and targeted vector control programs in Hidalgo state.

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Characterizing Spatial Patterns of Amazon Rainforest Wildfires and Driving Factors by Using Remote Sensing and GIS Geospatial Technologies

Known as the “lung of the planet”, the Amazon rainforest produces more than 20% of the Earth’s oxygen. Once a carbon pool for mitigating climate change, the Brazilian Amazônia Biome recently has become a significant carbon emitter due to increasingly frequent wildfires. Therefore, it is of crucial importance for authorities to understand wildfire dynamics to manage them safely and effectively. This study incorporated remote sensing and spatial statistics to study both the spatial distribution of wildfires during 2019 and their relationships to 15 environmental and anthropogenic factors. First, broad-scale spatial patterns of wildfire occurrence were explored using kernel density estimation, Moran’s I, Getis-Ord Gi*, and optimized hot spot analysis (OHSA). Second, the relationships between wildfire occurrence and the environmental and anthropogenic factors were explored using several regression models, including Ordinary Least Squares (OLS), global (quasi) Poisson, Geographically-weighted Gaussian Regression (GWGR), and Geographically-weighted Poisson Regression (GWPR). The spatial analysis results indicate that wildfires exhibited pronounced regional differences in spatial patterns in the vast and heterogeneous territory of the Amazônia Biome. The GWPR model outperformed the other regression models and explained the distribution and frequency of wildfires in the Amazônia Biome as a function of topographic, meteorologic, and environmental variables. Environmental factors like elevation, slope, relative humidity, and temperature were significant factors in explaining fire frequency in localized hotspots, while factors related to deforestation (forest loss, forest fragmentation measures, agriculture) explained wildfire activity over much of the region. Therefore, this study could improve a comprehensive study on, and understanding of, wildfire patterns and spatial variation in the target areas to support agencies as they prepare and plan for wildfire and land management activities in the Amazônia Biome.

Continent-wide modelling of potential habitats and connectivity for the Eurasian lynx (Lynx lynx) in Europe

Eurasian lynx (Lynx lynx) once inhabited almost the whole of the European continent. After facing nearly complete extinction about a century ago, they now form a more or less connected metapopulation with eleven broad-scale populations and numerous isolated habitat patches throughout Europe. Increasing public interest and a favourable legislative status by the EU give rise to hope for the return of the felide to parts of Central and Western Europe, where it is currently absent. In this context, a solid understanding of the overall suitability of the European landscape for a well-connected lynx population is crucial. Therefore, this work is looking into the current situation as well as potential habitats, ease of movement between those habitats, and potential future distribution, with the main focus on broad-scale spatial patterns. In addition to existing populations, eight habitat clusters were identified across Europe, using a modelling approach, rooted in a rule-based assessment accompanied by least-cost path identification, generating possible movement corridors. Key findings include large areas of potential habitat, yet overall low connectivity, with lynx movement restricted by a lack of forest cover as well as human land use, including mainly linear barriers like highways and dense road networks. This situation provides a number of challenges and opportunities for national and international conservation: The results clearly indicate that for a recolonisation of many parts of the European landscape reintroduction measures are indispensable in many parts of Europe. They also offer a first step towards a general understanding of how large carnivores like the Eurasian lynx might exist within a landscape increasingly shaped by anthropogenic actions and land use.

Spatial scale and structure of complex life cycle trematode parasite communities in streams.

By considering the role of site-level factors and dispersal, metacommunity concepts have advanced our understanding of the processes that structure ecological communities. In dendritic systems, like streams and rivers, these processes may be impacted by network connectivity and unidirectional current. Streams and rivers are central to the dispersal of many pathogens, including parasites with complex, multi-host life cycles. Patterns in parasite distribution and diversity are often driven by host dispersal. We conducted two studies at different spatial scales (within and across stream networks) to investigate the importance of local and regional processes that structure trematode (parasitic flatworms) communities in streams. First, we examined trematode communities in first-intermediate host snails (Elimia proxima) in a survey of Appalachian headwater streams within the Upper New River Basin to assess regional turnover in community structure. We analyzed trematode communities based on both morphotype (visual identification) and haplotype (molecular identification), as cryptic diversity in larval trematodes could mask important community-level variation. Second, we examined communities at multiple sites (headwaters and main stem) within a stream network to assess potential roles of network position and downstream drift. Across stream networks, we found a broad scale spatial pattern in morphotype- and haplotype-defined communities due to regional turnover in the dominant parasite type. This pattern was correlated with elevation, but not with any other environmental factors. Additionally, we found evidence of multiple species within morphotypes, and greater genetic diversity in parasites with hosts limited to in-stream dispersal. Within network parasite prevalence, for at least some parasite taxa, was related to several site-level factors (elevation, snail density and stream depth), and total prevalence decreased from headwaters to main stem. Variation in the distribution and diversity of parasites at the regional scale may reflect differences in the abilities of hosts to disperse across the landscape. Within a stream network, species-environment relationships may counter the effects of downstream dispersal on community structure.

A Likelihood Framework for Modeling Pairwise Beta Diversity Patterns Based on the Tradeoff Between Colonization and Extinction

Ecological communities are assembled by various mechanisms, including a tradeoff between colonization and extinction processes. However, it is still unclear how this tradeoff influences pairwise beta diversity pattern. Herein, we propose a novel likelihood framework to disentangle the compound impacts of species’ colonization and extinction rates on community-level compositional dissimilarity which are ignored by traditional indices. The framework infers two parameters of colonization and extinction rates, allowing ecologists to study their latitudinal or broad-scale spatial variation patterns and test the relative influences of associated environmental factors. More importantly, the likelihood-based model showed that multi-site beta diversity is essentially identical to the local colonization failure or extinction rate of species in newly colonized sites, but is not related to species’ colonization rates. Profoundly, the present likelihood model allows ecologists to explicitly infer the independent species’ colonization rate parameter and test its underpinning mechanisms, as it can be proven that this parameter would be only implicitly measured if used to compute multi-site beta diversity indices. KEYWORDS: beta diversity, island biogeography theory, ecological mechanisms, community assembly, biodiversity survey

Genetic diagnosis of a rare myrmecochorous species, Plagiorhegma dubium (Berberidaceae): Historical genetic bottlenecks and strong spatial structures among populations.

Distribution of genetic variation over time and space is relevant to demographic histories and tightly linked to ecological disturbances as well as evolutionary potential of an organism. Therefore, understanding the pattern of genetic diversity is a primary step in conservation and management projects for rare and threatened plant species. We used eight microsatellite markers to examine the level of genetic diversity, spatial structure, and demographic history of Plagiorhegma dubium, a rare myrmecochorous herb, populations sampled across northeast Asia and Siberia. We found low within‐population genetic variation associated with historical bottlenecks. Although pairwise F ST values were not much higher than the ones found in similar life form species, STRUCTURE and PCoA revealed a clear broadscale spatial pattern of genetic structure. Bayesian clustering (best K = 6) and PCoA identified three populations that are distinctive from neighboring populations in the Korean peninsula, which suggests potential units for conservation and management plans in Korea. MIGRATE‐N and BAYESASS showed that both contemporary (0.003–0.045) and historical migration rates (2 × e−5−4.6 × e−4) were low. Our findings provide a good example, where genetic considerations should be integrated for conservation and management plans of rare and threatened species.

Genetic diversity and structure of an endangered medicinal herb: implications for conservation.

Human-driven habitat fragmentation leads to spatial isolation of endangered plant species increasing extinction risk. Understanding genetic variability and population structure of rare and isolated plant species is of great importance for assessing extinction risk and setting up conservation plans. Aconitum austrokoreense, an endangered and endemic species in Korea, is a perennial herb commonly used for medicinal purposes. We used five nuclear microsatellites and one chloroplast marker to investigate genetic diversity and population structure for 479 individuals of A. austrokoreense from seven populations throughout South Korea. A multivariate approach, discriminant analysis of principal components analysis, revealed broad-scale spatial patterns of A. austrokoreense populations across three major mountains that were composed of seven genetically distinct subgroups. High pairwise FST values (mean FST = 0.35; highest FST = 0.55) suggested significant differentiation among populations. Overall within population genetic variation was low. Based on Mantel test, there was significant correlation between geographical and genetic distances indicating pattern of isolation by distance. Our results suggest that A. austrokoreense populations may have undergone recent population bottlenecks. Given the limited dispersal ability of the species and ongoing habitat fragmentation, population isolation may further be exacerbated leading to increased extinction risk.

Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western U.S.

Big sagebrush (Artemisia tridentata Nutt.) plant communities are widespread in western North America and, similar to all shrub steppe ecosystems worldwide, are composed of a shrub overstory layer and a forb and graminoid understory layer. Forbs account for the majority of plant species diversity in big sagebrush plant communities and are important for ecosystem function. Few studies have explored geographic patterns of forb species richness and composition and their relationships with environmental variables in these communities. Our objectives were to examine the fine and broad-scale spatial patterns in forb species richness and composition and the influence of environmental variables. We sampled forb species richness and composition along transects at 15 field sites in Colorado, Idaho, Montana, Nevada, Oregon, Utah, and Wyoming, built species-area relationships to quantify differences in forb species richness at sites, and used Principal Components Analysis, non-metric multidimensional scaling, and redundancy analysis to identify relationships among environmental variables and forb species richness and composition. We found that species richness was most strongly correlated with soil texture, while species composition was most related to climate. The combination of climate and soil texture influences water availability, which our results indicate has important consequences for forb species richness and composition, and suggests that climate change-induced modification of soil water availability may have important implications for plant species diversity in the future.

Distribution of unionid freshwater mussels and host fishes in Texas. A study of broad-scale spatial patterns across basins and a strong climate gradient

Unionid freshwater mussels are a threatened fauna, and understanding their distribution is essential to aid and promote conservation efforts. Therefore, we (1) compared patterns of species richness and endemism of Texas mussel and fish species, as mussels depend on fish for their reproduction and dispersal; (2) examined how distribution and community composition of mussels and fishes varies across river basins; and (3) how much variation in mussel community composition could be explained by the distribution of potential host fish, river basin (as a spatial component), ecoregion (as proxy for large-scale environmental differences), and flow variability. Mussel and fish community compositions in rivers differed significantly between river basins with an east-to-west gradient of decreasing species richness following the transition from sub-humid to arid climate. River basin explained 25% of the variation in mussel community composition, and potential host fish presence explained 20%. The total variation explained by both variables was 34%, as part of the variation in host fish presence (11.5%) was spatially structured by differences in river basins. Flow variability explained an additional 14% of the variation in mussel community composition, and ecoregion an additional 9% compared with river basin alone. Locations of significantly higher mussel species richness and/or endemism were present in rivers from all regions of Texas. These locations should be protected, especially as human population continues to expand and urbanize in these regions. A better understanding of mussel–host fish relationships and the impact of flow variation on the distribution of mussels will be needed to inform conservation efforts.

Pink sea fans (Eunicella verrucosa) as indicators of the spatial efficacy of Marine Protected Areas in southwest UK coastal waters

Globally, the need to identify and establish integrated and connected systems of Marine Protected Areas (MPAs) is becoming increasingly recognised. For best practice, these networks need to be planned and assessed against multiple criteria. However, building a sound evidence base to support decision-making processes is complex, as well as fiscally and logistically challenging. Recent studies have demonstrated the utility of integrating ‘citizen science’ data into mainstream scientific analysis, particularly where broad-scale spatial patterns of distribution are required. In UK waters, the pink sea fan (Eunicella verrucosa) is a nationally protected slow growing, cold-water coral, and is a representative species of reef features that provide habitat for many other sessile species. However, this species is vulnerable to physical impact and loss of suitable substratum, and is likely highly vulnerable to bottom-towed fishing gears. In this study, data from a volunteer-based marine survey programme (‘Seasearch’) are analysed with the aim of describing the spatial distribution and relative abundance of pink sea fan colonies throughout southwest UK coastal waters. The congruence between pink sea fans and the extant southern UK MPA network is reported, and the current threat from Bottom-Towed Gear (BTG) to pink sea fan dominated reefs, that have historically lacked protection, is quantitatively assessed. This analysis reveals that protection of this and other benthic species has been increased by management of previously ‘open access’ MPAs. Nonetheless, areas of pink sea fan habitat and their host reef systems exist outside extant protected areas in southwest UK seas, and as such are potentially at risk from bottom-towed fisheries. This analysis demonstrates the utility of well-organised citizen science data collection and highlights how such efforts can help inform knowledge on broad scale patterns of biodiversity.

Indicators of vegetation productivity under a changing climate in British Columbia, Canada

Understanding the relationship between vegetation and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing vegetation indicators derived from remotely sensed imagery, we present an approach to forecast shifts in the future distribution of vegetation. Remotely sensed metrics representing cumulative greenness, seasonality, and minimum cover have successfully been linked to species distributions over broad spatial scales. In this paper we developed models between a historical time series of Advanced Very High Resolution Radiometer (AVHRR) satellite imagery from 1987 to 2007 at 1 km spatial resolution with corresponding climate data using regression tree modeling approaches. We then applied these models to three climate change scenarios produced by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity indices in 2065. Our results indicated that warming may lead to increased cumulative greenness in northern British Columbia and seasonality in vegetation is expected to decrease for higher elevations, while levels of minimum cover increase. The Coast Mountains of the Pacific Maritime region and high elevation edge habitats across British Columbia were forecasted to experience the greatest amount of change. Our approach provides resource managers with information to mitigate and adapt to future habitat dynamics. Forecasting vegetation productivity levels presents a novel approach for understanding the future implications of climate change on broad scale spatial patterns of vegetation.

Broad-scale spatial patterns of canopy cover and pond morphology affect the structure of a Neotropical amphibian metacommunity

Spatial and environmental processes influence species composition at distinct scales. Previous studies suggested that the distribution of larval anurans at the landscape-scale is influenced by environmental gradients related to adult breeding site selection, such as pond canopy cover, but not by water chemistry. However, the combined effects of spatial, pond morphology, and water chemistry variables on metacommunity structure of larval anurans have not been analyzed yet. We used a partial redundancy analysis with variation partitioning to analyze the relative influence of pond morphology (e.g., depth, area, and aquatic vegetation), water chemistry, and spatial variables on a tadpole metacommunity from southeastern Brazil. We predict that pond morphology and canopy cover will influence the metacommunity at broad spatial scales, while water chemistry would play a larger role at finer scales. We found that broad-scale spatial patterns of pond canopy cover and pond morphology strongly influenced metacommunity structure, with water chemistry being not significant. Additionally, species composition was spatially autocorrelated at short distances. We suggest that the reproductive behavior of adult anurans is driving tadpole metacommunity dynamics, since pond morphology, but not water chemistry affects breeding site selection by adults. Our results contribute to the understanding of amphibian species diversity in tropical wetlands.

Hierarchical Dynamics of Ecological Communities: Do Scales of Space and Time Match?

Theory posits that community dynamics organize at distinct hierarchical scales of space and time, and that the spatial and temporal patterns at each scale are commensurate. Here we use time series modeling to investigate fluctuation frequencies of species groups within invertebrate metacommunities in 26 boreal lakes over a 20-year period, and variance partitioning analysis to study whether species groups with different fluctuation patterns show spatial signals that are commensurate with the scale-specific fluctuation patterns identified. We identified two groups of invertebrates representing hierarchically organized temporal dynamics: one species group showed temporal variability at decadal scales (slow patterns of change), whilst another group showed fluctuations at 3 to 5-year intervals (faster change). This pattern was consistently found across all lakes studied. A spatial signal was evident in the slow but not faster-changing species groups. As expected, the spatial signal for the slow-changing group coincided with broad-scale spatial patterns that could be explained with historical biogeography (ecoregion delineation, and dispersal limitation assessed through a dispersal trait analysis). In addition to spatial factors, the slow-changing groups correlated with environmental variables, supporting the conjecture that boreal lakes are undergoing environmental change. Taken together our results suggest that regionally distinct sets of taxa, separated by biogeographical boundaries, responded similarly to broad-scale environmental change. Not only does our approach allow testing theory about hierarchically structured space-time patterns; more generally, it allows assessing the relative role of the ability of communities to track environmental change and dispersal constraints limiting community structure and biodiversity at macroecological scales.

Impacts of Hypoxia on Zooplankton Spatial Distributions in the Northern Gulf of Mexico

The northern Gulf of Mexico (NGOMEX) was surveyed to examine the broad-scale spatial patterns and inter-relationships between hypoxia ( 2 mg L−1 dissolved oxygen), the daytime median depth of the water column zooplankton was on average 7 m deeper than the median depth of zooplankton in water columns with hypoxic bottom waters. A reduction in larger zooplankton when there were hypoxic bottom waters suggests that if zooplankton cannot migrate to deeper, darker water under hypoxic conditions, they may be more susceptible to size-selective predation by visual predators. Thus, habitat compression in the northern Gulf of Mexico due to hypoxic bottom water may have implications for trophic transfer by increasing the contact between predators and prey.

Latitudinal variation in morphological traits of the genus Pinus and its relation to environmental and phylogenetic signals

Background: Broad-scale analysis of interspecific trait variation is a fundamental approach in comparative ecology to investigate general species–environment relationships, but inferences from environmental and phylogenetic signals are still controversially discussed. Aims: The aim of this study was to globally analyse the genus Pinus and the interspecific variation of morphological traits with latitude as a surrogate of broad-scale environmental changes, and to compare latitudinal trait correlations with biogeographic, environmental and phylogenetic signals in trait variation. Methods: Based on native range maps of 103 Pinus species, the latitudinal correlations of nine morphological traits, including needle characters, cone length and tree height were calculated. Principal component analysis was used to explore trait covariation. Variation partitioning was applied to disentangle environmental and phylogenetic signals in trait variation. Results: Strong latitudinal correlations were detected for traits, such as needle length:width ratio or needle longevity, with similar trends for different taxonomic species subsets and geographic regions. Strong latitudinal correlations were related to a decrease in the pure phylogenetic signal and to an increase in the phylogenetically structured environmental variation (PSEV), whereas the pure environmental signal was almost negligible. Conclusions: Besides a ranking of traits that differ in environmental and phylogenetic signals, our results showed a general relationship between increasing latitudinal trait correlation and an increase in PSEV, which indicates phylogenetic niche conservatism. Thus, for the investigated morphological traits of the genus Pinus both environmental and phylogenetic signals are directly linked by PSEV to broad-scale spatial patterns in trait variation.

Combining Satellite-Based Fire Observations and Ground-Based Lightning Detections to Identify Lightning Fires Across the Conterminous USA

Lightning fires are a common natural disturbance in North America, and account for the largest proportion of the area burned by wildfires each year. Yet, the spatiotemporal patterns of lightning fires in the conterminous US are not well understood due to limitations of existing fire databases. Our goal here was to develop and test an algorithm that combined MODIS fire detections with lightning detections from the National Lightning Detection Network to identify lightning fires across the conterminous US from 2000 to 2008. The algorithm searches for spatiotemporal conjunctions of MODIS fire clusters and NLDN detected lightning strikes, given a spatiotemporal lag between lightning strike and fire ignition. The algorithm revealed distinctive spatial patterns of lightning fires in the conterminous US While a sensitivity analysis revealed that the algorithm is highly sensitive to the two thresholds that are used to determine conjunction, the density of fires it detected was moderately correlated with ground based fire records. When only fires larger than 0.4 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> were considered, correlations were higher and the root-mean-square error between datasets was less than five fires per 625 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> for the entire study period. Our algorithm is thus suitable for detecting broad scale spatial patterns of lightning fire occurrence, and especially lightning fire hotspots, but has limited detection capability of smaller fires because these cannot be consistently detected by MODIS. These results may enhance our understanding of large scale patterns of lightning fire activity, and can be used to identify the broad scale factors controlling fire occurrence.

Broad-scale spatial pattern of forest landscape types in the Guiana Shield

Detecting broad scale spatial patterns across the South American rainforest biome is still a major challenge. Although several countries do possess their own, more or less detailed land-cover map, these are based on classifications that appear largely discordant from a country to another. Up to now, continental scale remote sensing studies failed to fill this gap. They mostly result in crude representations of the rainforest biome as a single, uniform vegetation class, in contrast with open vegetations. A few studies identified broad scale spatial patterns, but only when they managed to map a particular forest characteristic such as biomass. The main objective of this study is to identify, characterize and map distinct forest landscape types within the evergreen lowland rainforest at the sub-continental scale of the Guiana Shield (north-east tropical South-America 10° North-2° South; 66° West-50° West). This study is based on the analysis of a 1-year daily data set (from January 1st to December 31st, 2000) from the VEGETATION sensor onboard the SPOT-4 satellite (1-km spatial resolution). We interpreted remotely sensed landscape classes (RSLC) from field and high resolution remote sensing data of 21 sites in French Guiana. We cross-analyzed remote sensing data, field observations and environmental data using multivariate analysis. We obtained 33 remotely sensed landscape classes (RSLC) among which five forest-RSLC representing 78% of the forested area. The latter were classified as different broad forest landscape types according to a gradient of canopy openness. Their mapping revealed a new and meaningful broad-scale spatial pattern of forest landscape types. At the scale of the Guiana Shield, we observed a spatial patterns similarity between climatic and forest landscape types. The two most open forest-RSLCs were observed mainly within the north-west to south-east dry belt. The three other forest-RSLCs were observed in wetter and less anthropized areas, particularly in the newly recognized “Guianan dense forest arch”. Better management and conservation policies, as well as improvement of biological and ecological knowledge, require accurate and stable representations of the geographical components of ecosystems. Our results represent a decisive step in this way for the Guiana Shield area and contribute to fill one of the major shortfall in the knowledge of tropical forests.